Regularized Ultrasound Phantom-Free Local Attenuation Coefficient Slope (ACS) Imaging in Homogeneous and Heterogeneous Tissues

Abstract

Attenuation map or measurements based on local attenuation coefficient slope (ACS) in quantitative ultrasound (QUS) has shown potential for diagnosis of liver steatosis. In liver cancers, tissue abnormalities and tumors detected using ACS are also of interest to provide new image contrast to clinicians. Current phantom-based approaches have the limitation of assuming comparable speed of sound between the reference phantom and insonified tissues. Moreover, these methods present the inconvenience for operators to acquire data on phantoms as well as on patients. The main goal was to alleviate these drawbacks by proposing a methodology for constructing phantom-free regularized (PF-R) local ACS maps and investigate the performance in both homogeneous and heterogeneous media. The proposed method was tested on two tissue mimicking media with different ACS constructed as homogeneous phantoms, side-byside and top-to-bottom phantoms, and inclusion phantoms with different attenuations. Moreover, an in-vivo proof-of-concept was performed on healthy, steatotic and cancerous human liver datasets. Modifications brought to previous works include: a) a linear interpolation of the power spectrum in log-scale; b) the relaxation of the underlying hypothesis on the diffraction factor; c) a generalization to nonhomogeneous local ACS; and d) an adaptive restriction of frequencies to a more reliable range than the usable frequency range. Regularization was formulated as a generalized LASSO, and a variant of the Bayesian Information Criterion (BIC) was applied to estimate the Lagrangian multiplier on the LASSO constraint. In addition, we evaluated the proposed algorithm when applying median filtering before and after regularization. Tests conducted showed that the PF-R yielded robust results in all tested conditions, suggesting potential for additional validation as a diagnosis method.

Reference-phantom-free imaging of local attenuation coefficient in synthetic transmit aperture ultrasound imaging

“…This enhanced SNR, as achieved by our method, is pivotal as it directly translates to more accurate and reliable estimations of attenuation coefficients. In the future, we can explore the feasibility of reducing the window size with parametric regularization [20] to improve spatial resolution.…”

“…Additionally, we will investigate reducing the computation load of the method so that it can be used for clinical investigations. A comparison between the current B-mode methods (spectral-based methods) [20] and the proposed STA method will be made.…”

“…Despite its effectiveness, the requirement for a predefined frequency range and the use of a large analysis window of 2.5 cm length can limit its feasibility in detecting lesions and other abnormalities within heterogeneous media. Rafati [20] applied the reference frequency method to homogeneous and heterogeneous phantoms with parametric regularization to reduce image artifacts. Such limitations emphasize the continuous need for methodological advancements in this field, especially as the complexity and variability of clinical scenarios increase.…”

Spectral-based Quantitative Ultrasound Imaging Processing Techniques: Comparisons of RF Versus IQ Approaches

“…Quantitative ultrasound (QUS) is an imaging technique which includes spectral-based parameterization, elastography, shear wave imaging, flow estimation and envelope statistics. 1 Many studies have demonstrated that QUS is useful in tissue characterization with liver disease, 2–5 breast cancer, 6–8 thermal treatment, 9 and thyroid cancer. 10 In terms of spectral-based QUS, the backscatter coefficient (BSC) and attenuation coefficient slope (ACS) are frequently utilized because they can be system-independent parameters and are fundamental properties of tissues.…”

Reference-phantom-free imaging of local attenuation coefficient in synthetic transmit aperture ultrasound imaging

“…Despite its effectiveness, the requirement for a predefined frequency range and the use of a large analysis window of 2.5 cm length can limit its feasibility in detecting lesions and other abnormalities within heterogeneous media. Rafati [20] applied the reference frequency method to homogeneous and heterogeneous phantoms with parametric regularization to reduce image artifacts. Such limitations emphasize the continuous need for methodological advancements in this field, especially as the complexity and variability of clinical scenarios increase.…”